Task-dependent influence of genetic architecture and mating frequency on division of labour in social insect societies.

Division of labour is one of the most prominent features of social insects. The efficient allocation of individuals to different tasks requires dynamic adjustment in response to environmental perturbations. Theoretical models suggest that the colony-level flexibility in responding to external changes and internal perturbation may depend on the within-colony genetic diversity, which is affected by the number of breeding individuals. However, these models have not considered the genetic architecture underlying the propensity of workers to perform the various tasks. Here, we investigated how both within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes influencing the stimulus (threshold) for a given task at which workers begin to perform that task jointly influence task allocation efficiency. We used a numerical agent-based model to investigate the situation where workers had to perform either a regulatory task or a foraging task. One hundred generations of artificial selection in populations consisting of 500 colonies revealed that an increased number of matings always improved colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or a few genes for the foraging task's threshold. By contrast, a higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes encoding the threshold for the regulatory task only had a minor effect on colony performance. Overall, our numerical experiments support the importance of mating frequency on efficiency of division of labour and also reveal complex interactions between the number of matings and genetic architecture.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

The fine-scale architecture of structural variants in 17 mouse genomes.

BACKGROUND: Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. RESULTS: By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. CONCLUSIONS: An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.

The heterotetrameric architecture of the epithelial sodium channel (ENaC).

The epithelial sodium channel (ENaC) is a key element for the maintenance of sodium balance and the regulation of blood pressure. Three homologous ENaC subunits (alpha, beta and gamma) assemble to form a highly Na+-selective channel. However, the subunit stoichiometry of ENaC has not yet been solved. Quantitative analysis of cell surface expression of ENaC alpha, beta and gamma subunits shows that they assemble according to a fixed stoichiometry, with alpha ENaC as the most abundant subunit. Functional assays based on differential sensitivities to channel blockers elicited by mutations tagging each alpha, beta and gamma subunit are consistent with a four subunit stoichiometry composed of two alpha, one beta and one gamma. Expression of concatameric cDNA constructs made of different combinations of ENaC subunits confirmed the four subunit channel stoichiometry and showed that the arrangement of the subunits around the channel pore consists of two alpha subunits separated by beta and gamma subunits.

Precursor-product relationship between vitellogenin and the yolk proteins as derived from the complete sequence of a Xenopus vitellogenin gene.

In Xenopus laevis four estrogen-responsive genes are expressed simultaneously to produce vitellogenin, the precursor of the yolk proteins. One of these four genes, the gene A2, was sequenced completely, as well as cDNAs representing 75% of the coding region of the gene. From this data the exon-intron structure of the gene was established, revealing 35 exons that give a transcript of 5,619 bp without the poly A-tail. This A2 transcript encodes a vitellogenin of 1,807 amino acids, whose structure is discussed with respect to its function. At the nucleic acid as well as at the protein level no extensive homologies with any sequences other than vitellogenin were observed. Comparison of the amino acid sequence of the vitellogenin A2 molecule with biochemical data obtained from the different yolk proteins allowed us to localize the cleavage products on the vitellogenin precursor as follows: NH2 - lipovitellin I - phosvitin (or phosvette II - phosvette I) - lipovitellin II - COOH.

Mutations in the SPARC-Related Modular Calcium-Binding Protein 1 Gene, SMOC1, Cause Waardenburg Anophthalmia Syndrome.

Waardenburg anophthalmia syndrome, also known as microphthalmia with limb anomalies, ophthalmoacromelic syndrome, and anophthalmia-syndactyly, is a rare autosomal-recessive developmental disorder that has been mapped to 10p11.23. Here we show that this disease is heterogeneous by reporting on a consanguineous family, not linked to the 10p11.23 locus, whose two affected children have a homozygous mutation in SMOC1. Knockdown experiments of the zebrafish smoc1 revealed that smoc1 is important in eye development and that it is expressed in many organs, including brain and somites.

The shared allelic architecture of adiponectin levels and coronary artery disease.

OBJECTIVE: A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. METHODS: Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium (n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium (n = 85,274). RESULTS: In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing (P < 4.4 × 10(-4)). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD (P = 5.4 × 10(-7)). CONCLUSION: These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

Defining the role of common variation in the genomic and biological architecture of adult human height.

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Tumor architecture exerts no bias on nuclear grading in breast cancer diagnosis.

We recently reported that nuclear grading in prostate cancer is subject to a strong confirmation bias induced by the tumor architecture. We now wondered whether a similar bias governs nuclear grading in breast carcinoma. An unannounced test was performed at a pathology conference. Pathologists were asked to grade nuclei in a PowerPoint presentation. Circular high power fields of 27 invasive ductal carcinomas were shown, superimposed over low power background images of either tubule-rich or tubule-poor carcinomas. We found (a) that diagnostic reproducibility of nuclear grades was poor to moderate (weighed kappa values between 0.07 and 0.54, 27 cases, 44 graders), but (b) that nuclear grades were not affected by the tumor architecture. We speculate that the categorized grading in breast cancer, separating tubule formation, nuclear pleomorphism, and mitotic figure counts in a combined three tier score, prevents the bias that architecture exerts on nuclear grades in less well-controlled situations.

Equine herpesvirus-2 E10 gene product, but not its cellular homologue, activates NF-kappaB transcription factor and c-Jun N-terminal kinase.

We have previously reported on the death effector domain containing E8 gene product from equine herpesvirus-2, designated FLICE inhibitory protein (v-FLIP), and on its cellular homologue, c-FLIP, which inhibit the activation of caspase-8 by death receptors. Here we report on the structure and function of the E10 gene product of equine herpesvirus-2, designated v-CARMEN, and on its cellular homologue, c-CARMEN, which contain a caspase-recruiting domain (CARD) motif. c-CARMEN is highly homologous to the viral protein in its N-terminal CARD motif but differs in its C-terminal extension. v-CARMEN and c-CARMEN interact directly in a CARD-dependent manner yet reveal different binding specificities toward members of the tumor necrosis factor receptor-associated factor (TRAF) family. v-CARMEN binds to TRAF6 and weakly to TRAF3 and, upon overexpression, potently induces the c-Jun N-terminal kinase (JNK), p38, and nuclear factor (NF)-kappaB transcriptional pathways. c-CARMEN or truncated versions thereof do not appear to induce JNK and NF-kappaB activation by themselves, nor do they affect the JNK and NF-kappaB activating potential of v-CARMEN. Thus, in contrast to the cellular homologue, v-CARMEN may have additional properties in its unique C terminus that allow for an autonomous activator effect on NF-kappaB and JNK. Through activation of NF-kappaB, v-CARMEN may regulate the expression of the cellular and viral genes important for viral replication.